Software Quadrants: Centrality of Packages in Biomedical Research Dependencies

A 9.5 KB graph dataset from figshare, last updated on 2026-05-13. It maps upstream software dependencies used in biomedical papers to identify critical packages. The analysis, by Eva Maxfield Brown, proposes centrality metrics for software ecosystems like PyPi, CRAN, and Bioconductor.

Use Cases

• Identify foundational software libraries based on dependency network centrality described in the analysis.
• Map the upstream dependencies of software used in biomedical research papers as outlined in the work.
• Analyze and compare the structure of software ecosystems like PyPi, CRAN, and Bioconductor using proposed centrality metrics.
• Support decisions for software funding and recognition by highlighting critical but hidden packages.

Strengths

• Dataset is small (9.5 KB), facilitating quick download and initial exploration.
• Uses the CZ Software Mentions Dataset, a specific source for scientific software mentions.
• Explicitly analyzes three major software ecosystems: PyPi, CRAN, and Bioconductor.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

CZ Software Mentions Dataset

Collection Method

Analysis of upstream dependencies from software used in biomedical papers.

Freshness

Last updated 2026-05-13 17:51:31; freshness should be verified.